Rare Helium-Bearing Compound FeO2He Stabilized at Deep-Earth Conditions

There is compelling geochemical evidence for primordial helium trapped in Earth’s lower mantle, but the origin and nature of the helium source remain elusive due to scarce knowledge on viable helium-bearing compounds that are extremely rare. Here we explore materials physics underlying this prominent challenge. Our structure searches in conjunction with first-principles energetic and thermodynamic calculations uncover a remarkable helium-bearing compound FeO2He at high pressure-temperature conditions relevant to the core-mantle boundary. Calculated sound velocities consistent with seismic data validate FeO2He as a feasible constituent in ultralow velocity zones at the lowermost mantle. These mutually corroborating findings establish the first and hitherto only helium-bearing compound viable at pertinent geophysical conditions, thus providing vital physics mechanisms and materials insights for elucidating the enigmatic helium reservoir in deep Earth

Diverse biological effects of glycosyltransferase genes from Tartary buckwheat

Background: Tartary buckwheat (Fagopyrum tataricum) is an edible cereal crop whose sprouts have been marketed and commercialized for their higher levels of anti-oxidants, including rutin and anthocyanin. UDP-glucose flavonoid glycosyltransferases (UFGTs) play an important role in the biosynthesis of flavonoids in plants. So far, few studies are available on UFGT genes that may play a role in tartary buckwheat flavonoids biosynthesis. Here, we report on the identification and functional characterization of seven UFGTs from tartary buckwheat that are potentially involved in flavonoid biosynthesis (and have varying effects on plant growth and development when overexpressed in Arabidopsis thaliana.) Results: Phylogenetic analysis indicated that the potential function of the seven FtUFGT proteins, FtUFGT6, FtUFGT7, FtUFGT8, FtUFGT9, FtUFGT15, FtUFGT40, and FtUFGT41, could be divided into three Arabidopsis thaliana functional subgroups that are involved in flavonoid biosynthesis of and anthocyanin accumulation. A significant positive correlation between FtUFGT8 and FtUFGT15 expression and anthocyanin accumulation capacity was observed in the tartary buckwheat seedlings after cold stress. Overexpression in Arabidopsis thaliana showed that FtUFGT8, FtUFGT15, and FtUFGT41 significantly increased the anthocyanin content in transgenic plants. Unexpectedly, overexpression of FtUFGT6, while not leading to enhanced anthocyanin accumulation, significantly enhanced the growth yield of transgenic plants. When wild-type plants have only cotyledons, most of the transgenic plants of FtUFGT6 had grown true leaves. Moreover, the growth speed of the oxFtUFGT6 transgenic plant root was also significantly faster than that of the wild type. At later growth, FtUFGT6 transgenic plants showed larger leaves, earlier twitching times and more tillers than wild type, whereas FtUFGT15 showed opposite results. Conclusions: Seven FtUFGTs were isolated from tartary buckwheat. FtUFGT8, FtUFGT15, and FtUFGT41 can significantly increase the accumulation of total anthocyanins in transgenic plants. Furthermore, overexpression of FtUFGT6 increased the overall yield of Arabidopsis transgenic plants at all growth stages. However, FtUFGT15 shows the opposite trend at later growth stage and delays the growth speed of plants. These results suggested that the biological function of FtUFGT genes in tartary buckwheat is diverse

Neural 3D Video Synthesis

We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet expressive representation that enables high-quality view synthesis and motion interpolation. Our approach takes the high quality and compactness of static neural radiance fields in a new direction: to a model-free, dynamic setting. At the core of our approach is a novel time-conditioned neural radiance fields that represents scene dynamics using a set of compact latent codes. To exploit the fact that changes between adjacent frames of a video are typically small and locally consistent, we propose two novel strategies for efficient training of our neural network: 1) An efficient hierarchical training scheme, and 2) an importance sampling strategy that selects the next rays for training based on the temporal variation of the input videos. In combination, these two strategies significantly boost the training speed, lead to fast convergence of the training process, and enable high quality results. Our learned representation is highly compact and able to represent a 10 second 30 FPS multi-view video recording by 18 cameras with a model size of just 28MB. We demonstrate that our method can render high-fidelity wide-angle novel views at over 1K resolution, even for highly complex and dynamic scenes. We perform an extensive qualitative and quantitative evaluation that shows that our approach outperforms the current state of the art. We include additional video and information at: https://neural-3d-video.github.io/Comment: Project website: https://neural-3d-video.github.io

Lithium Subhydrides Under Pressure and their Superatom-Like Building Blocks

Evolutionary structure searches are used to predict a new class of compounds in the lithium--rich region of the lithium/hydrogen phase diagram under pressure. First principles computations show that LimH, 4<m<9, are stabilized with respect to LiH and Li between 50-100 GPa. The building block of all of the lithium subhydrides is an Li8H cluster, which can be thought of as a superalkali. The geometries and electronic structures of these phases is analogous to that of the well-known alkali metal suboxides.Comment: ChemPlusChem, accepte

Mapping photonic entanglement into and out of a quantum memory

Recent developments of quantum information science critically rely on entanglement, an intriguing aspect of quantum mechanics where parts of a composite system can exhibit correlations stronger than any classical counterpart. In particular, scalable quantum networks require capabilities to create, store, and distribute entanglement among distant matter nodes via photonic channels. Atomic ensembles can play the role of such nodes. So far, in the photon counting regime, heralded entanglement between atomic ensembles has been successfully demonstrated via probabilistic protocols. However, an inherent drawback of this approach is the compromise between the amount of entanglement and its preparation probability, leading intrinsically to low count rate for high entanglement. Here we report a protocol where entanglement between two atomic ensembles is created by coherent mapping of an entangled state of light. By splitting a single-photon and subsequent state transfer, we separate the generation of entanglement and its storage. After a programmable delay, the stored entanglement is mapped back into photonic modes with overall efficiency of 17 %. Improvements of single-photon sources together with our protocol will enable "on demand" entanglement of atomic ensembles, a powerful resource for quantum networking.Comment: 7 pages, and 3 figure

Long-term ambient air pollution exposure and cardio-respiratory disease in China: findings from a prospective cohort study

Background Existing evidence on long-term ambient air pollution (AAP) exposure and risk of cardio-respiratory diseases in China is mainly on mortality, and based on area average concentrations from fixed-site monitors for individual exposures. Substantial uncertainty persists, therefore, about the shape and strength of the relationship when assessed using more personalised individual exposure data. We aimed to examine the relationships between AAP exposure and risk of cardio-respiratory diseases using predicted local levels of AAP. Methods A prospective study included 50,407 participants aged 30–79 years from Suzhou, China, with concentrations of nitrogen dioxide (NO2), sulphur dioxide (SO2), fine (PM2.5), and inhalable (PM10) particulate matter, ozone (O3) and carbon monoxide (CO) and incident cases of cardiovascular disease (CVD) (n = 2,563) and respiratory disease (n = 1,764) recorded during 2013–2015. Cox regression models with time-dependent covariates were used to estimate adjusted hazard ratios (HRs) for diseases associated with local-level concentrations of AAP exposure, estimated using Bayesian spatio–temporal modelling. Results The study period of 2013–2015 included a total of 135,199 person-years of follow-up for CVD. There was a positive association of AAP, particularly SO2 and O3, with risk of major cardiovascular and respiratory diseases. Each 10 µg/m3 increase in SO2 was associated with adjusted hazard ratios (HRs) of 1.07 (95% CI: 1.02, 1.12) for CVD, 1.25 (1.08, 1.44) for COPD and 1.12 (1.02, 1.23) for pneumonia. Similarly, each 10 µg/m3 increase in O3 was associated with adjusted HR of 1.02 (1.01, 1.03) for CVD, 1.03 (1.02, 1.05) for all stroke, and 1.04 (1.02, 1.06) for pneumonia. Conclusions Among adults in urban China, long-term exposure to ambient air pollution is associated with a higher risk of cardio-respiratory disease

The catalytic subunit of the system L1 amino acid transporter (S<i>lc7a5</i>) facilitates nutrient signalling in mouse skeletal muscle

The System L1-type amino acid transporter mediates transport of large neutral amino acids (LNAA) in many mammalian cell-types. LNAA such as leucine are required for full activation of the mTOR-S6K signalling pathway promoting protein synthesis and cell growth. The SLC7A5 (LAT1) catalytic subunit of high-affinity System L1 functions as a glycoprotein-associated heterodimer with the multifunctional protein SLC3A2 (CD98). We generated a floxed Slc7a5 mouse strain which, when crossed with mice expressing Cre driven by a global promoter, produced Slc7a5 heterozygous knockout (Slc7a5+/-) animals with no overt phenotype, although homozygous global knockout of Slc7a5 was embryonically lethal. Muscle-specific (MCK Cre-mediated) Slc7a5 knockout (MS-Slc7a5-KO) mice were used to study the role of intracellular LNAA delivery by the SLC7A5 transporter for mTOR-S6K pathway activation in skeletal muscle. Activation of muscle mTOR-S6K (Thr389 phosphorylation) in vivo by intraperitoneal leucine injection was blunted in homozygous MS-Slc7a5-KO mice relative to wild-type animals. Dietary intake and growth rate were similar for MS-Slc7a5-KO mice and wild-type littermates fed for 10 weeks (to age 120 days) with diets containing 10%, 20% or 30% of protein. In MS-Slc7a5-KO mice, Leu and Ile concentrations in gastrocnemius muscle were reduced by ∼40% as dietary protein content was reduced from 30 to 10%. These changes were associated with >50% decrease in S6K Thr389 phosphorylation in muscles from MS-Slc7a5-KO mice, indicating reduced mTOR-S6K pathway activation, despite no significant differences in lean tissue mass between groups on the same diet. MS-Slc7a5-KO mice on 30% protein diet exhibited mild insulin resistance (e.g. reduced glucose clearance, larger gonadal adipose depots) relative to control animals. Thus, SLC7A5 modulates LNAA-dependent muscle mTOR-S6K signalling in mice, although it appears non-essential (or is sufficiently compensated by e.g. SLC7A8 (LAT2)) for maintenance of normal muscle mass

Heterogeneity in the diagnosis and prognosis of ischemic stroke subtypes: 9-year follow-up of 22,000 cases in Chinese adults

Background: Reliable classification of ischemic stroke (IS) etiological subtypes is required in research and clinical practice, but the predictive properties of these subtypes in population studies with incomplete investigations are poorly understood. Aims: To compare the prognosis of etiologically classified IS subtypes and use machine learning (ML) to classify incompletely investigated IS cases. Methods: In a 9-year follow-up of a prospective study of 512,726 Chinese adults, 22,216 incident IS cases, confirmed by clinical adjudication of medical records, were assigned subtypes using a modified Causative Classification System for Ischemic Stroke (CCS) (large artery atherosclerosis (LAA), small artery occlusion (SAO), cardioaortic embolism (CE), or undetermined etiology) and classified by CCS as “evident,” “probable,” or “possible” IS cases. For incompletely investigated IS cases where CCS yielded an undetermined etiology, an ML model was developed to predict IS subtypes from baseline risk factors and screening for cardioaortic sources of embolism. The 5-year risks of subsequent stroke and all-cause mortality (measured using cumulative incidence functions and 1 minus Kaplan–Meier estimates, respectively) for the ML-predicted IS subtypes were compared with etiologically classified IS subtypes. Results: Among 7443 IS subtypes with evident or probable etiology, 66% had SAO, 32% had LAA, and 2% had CE, but proportions of SAO-to-LAA cases varied by regions in China. CE had the highest rates of subsequent stroke and mortality (43.5% and 40.7%), followed by LAA (43.2% and 17.4%) and SAO (38.1% and 11.1%), respectively. ML provided classifications for cases with undetermined etiology and incomplete clinical data (24% of all IS cases; n = 5276), with area under the curves (AUC) of 0.99 (0.99–1.00) for CE, 0.67 (0.64–0.70) for LAA, and 0.70 (0.67–0.73) for SAO for unseen cases. ML-predicted IS subtypes yielded comparable subsequent stroke and all-cause mortality rates to the etiologically classified IS subtypes. Conclusion: This study highlighted substantial heterogeneity in prognosis of IS subtypes and utility of ML approaches for classification of IS cases with incomplete clinical investigations